AIMC Topic: Refuse Disposal

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Ecotoxicological impacts of landfill sites: Towards risk assessment, mitigation policies and the role of artificial intelligence.

The Science of the total environment Mar 20, 2024
Waste disposal in landfills remains a global concern. Despite technological developments, landfill leachate poses a hazard to ecosystems and human health since it acts as a secondary reservoir for legacy and emerging pollutants. This study provides a...
Risk Assessment Environmental Monitoring Humans Artificial Intelligence Refuse Disposal Waste Disposal Facilities Ecotoxicology Water Pollutants, Chemical Environmental Policy
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Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Waste management (New York, N.Y.) Feb 24, 2024
Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to ...
Solid Waste Waste Management Refuse Disposal Machine Learning Neural Networks, Computer Fertilizers Soil Composting
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Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction.

Environmental pollution (Barking, Essex : 1987) Jan 17, 2024
Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine le...
Neural Networks, Computer Machine Learning Solid Waste Waste Management Greenhouse Gases Carbon Air Pollutants Refuse Disposal
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Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Aug 28, 2023
Prediction of municipal solid waste (MSW) generation plays an essential role in effective waste management. The main objectives of this study were to develop models for accurate prediction of MSW generation (MSWG) and analyze the influence of dominan...
Population Density Refuse Disposal Cities Models, Theoretical Solid Waste Waste Management Machine Learning China Neural Networks, Computer
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Garbage detection and classification using a new deep learning-based machine vision system as a tool for sustainable waste recycling.

Waste management (New York, N.Y.) Mar 28, 2023
Waste recycling is a critical issue for environment pollution management while garbage classification determines the recycling efficiency. In order to reduce labor costs and increase garbage classification capacity, a machine vision system is establi...
Garbage Deep Learning Waste Management Refuse Disposal Recycling
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Prediction of the proximate analysis parameters of refuse-derived fuel based on deep learning approach.

Environmental science and pollution research international Oct 4, 2022
Determination of proximate characteristics can be achieved using conventional analyses methods that require a certain amount of time. In cement factories, refuse-derived fuel (RDF) is continuously fed to a kiln by a conveyor belt, so even if an inapp...
Garbage Deep Learning Refuse Disposal Spectroscopy, Near-Infrared
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Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method.

Environmental science and pollution research international Sep 19, 2022
Fastest growing population, rapid urbanization, and growth in the disciplines of science and technology cause continually development in the amount and diversity of solid waste. In modern world, evaluation of an appropriate solid waste disposal metho...
Decision Making Solid Waste Entropy Uncertainty Fuzzy Logic Refuse Disposal
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Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai.

Chemosphere Aug 20, 2022
It is crucial to precisely estimate the municipal solid waste (MSW) amount for its sustainable management. Owing to learning complicated and abstract features between the factors and target, deep learning has recently emerged as one of the useful too...
Cities Solid Waste Deep Learning Waste Management Humans Refuse Disposal China
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Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies.

Critical reviews in food science and nutrition Aug 11, 2022
Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, amo...
Refuse Disposal Technology Food Humans Artificial Intelligence Pandemics
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Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation.

International journal of food microbiology Apr 28, 2022
It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the world. Inception of modern techniques like omics (metagenomics, proteomics, transcriptomics, wasteomics,...
Food Supply Food Child Refuse Disposal Humans Agriculture Artificial Intelligence
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